Firms are moving from decoupled decision making processes toward more coordinated and integrated design and control of all of their components in order to provide goods and services to the customer at a low cost and high service levels. These need new approach, supply chain management. This thesis deals with an integration problem of a traditional dynamic lot-sizing and distribution planning problem in a supply chain network. To solve integrated model efficiently, the capacity constraint is ignored and distribution problem is simplified to the dynamic transportation routing model. Objective function consists of inventory-holding costs, transportation costs, production costs, and set-up costs and the model is constrained by inventory-balancing constraints, set-up related constraints, and route related constraints. A solution technique based on the Benders decomposition is developed and tested with various examples. Experimental tests show that the algorithm solves problems within reasonable time and solutions within 5% gap were found. The proposed BD algorithm is tend to be more suitable for the case where low inventory-holding costs and high set-up costs are used.